code: def _scatter_plot(ax, X, array_of_markers, axis_plot=True):
      # `marker` parameter does not support list or array format, needs a loop
      for i, marker in enumerate(array_of_markers):
          ax.scatter(
              X[i, 0],
              X[i, 1],
              X[i, 2],
              s=26,
              marker=marker,
              alpha=0.8,
              color=tuple(X[i] / 255),
          )
      if axis_plot == True:
          ax.set_xlabel("Red")
          ax.set_ylabel("Green")
          ax.set_zlabel("Blue")
      else:
          ax.set_axis_off()
      ax.grid(False)
      ax.view_init(elev=6.0, azim=-22.0)
  
file_path: networkx/examples/algorithms/plot_image_segmentation_spectral_graph_partiion.py
imports: import numpy
  import networkx
  import matplotlib.pyplot
  from matplotlib import animation
  from matplotlib.lines import Line2D
  from sklearn.cluster import SpectralClustering
label_desc: Use image node_id 1 for calling a global function with example usage: _scatter_plot(ax, X, array_of_markers, axis_plot) without return types